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Publications of SPCL

S. Cao, S. Di Girolamo, T. Hoefler:
	Accelerating Data Serialization/Deserialization Protocols with In-Network Compute (In 2022 IEEE/ACM International Workshop on Exascale MPI (ExaMPI), Nov. 2022) Abstract Efficient data communication is a major goal for scalable and cost-effective use of datacenter and HPC system resources. To let applications communicate efficiently, exchanged data must be serialized at the source and deserialized at the destination. The serialization/deserialization process enables exchanging data in a language- and machine-independent format. However, serialization/deserialization overheads can negatively impact application performance. For example, a server within a microservice framework must deserialize all incoming requests before invoking the respective microservices. We show how data deserialization can be offloaded to fully programmable Smart-NICs and performed on the data path, on a per-packet basis. This solution avoids intermediate memory copies, enabling on-the-fly deserialization. We showcase our approach by offloading Google Protocol Buffers, a widely used framework to serialize/deserialize data. Our evaluation demonstrates that, by offloading data deserialization to the NIC, we can achieve up to 4.8x higher throughput than a single AMD Ryzen 7 CPU. We then show through microservice throughput modeling how we can improve the overall throughput by pipelining the deserialization and actual application activities with PsPIN. Documents download article: download slides: Recorded talk (best effort)
	BibTeX
@inproceedings{,   author={Shiyi Cao and Salvatore Di Girolamo and Torsten Hoefler},   title={{Accelerating Data Serialization/Deserialization Protocols with In-Network Compute}},   year={2022},   month={11},   booktitle={2022 IEEE/ACM International Workshop on Exascale MPI (ExaMPI)},   doi={10.1109/ExaMPI56604.2022.00008}, }